Relative positioning method and device based on point cloud registration, equipment and medium

Abstract

The application provides a relative positioning method and device based on point cloud registration, equipment and medium, first point cloud data of a shore bridge is acquired; the first point cloud data of the shore bridge is registered with a pre-acquired shore bridge point cloud map, second point cloud data corresponding to the first point cloud data after registration is obtained; a first current position of a vehicle is acquired, and the first current position and the second point cloud data are used to determine a first coordinate position of the vehicle in a shore bridge coordinate system, the shore bridge point cloud map comprises a coordinate position of the shore bridge in the shore bridge coordinate system; the first coordinate position is converted according to a pre-acquired coordinate position of the shore bridge in a wharf coordinate system, and a second coordinate position of the vehicle in the wharf coordinate system is obtained. The application embodiment can improve the accuracy of vehicle positioning.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automatic driving, in particular to a relative positioning method and device based on point cloud registration, equipment and medium. BACKGROUND

[0002] In order to improve the accuracy of vehicle positioning, vehicles are mostly provided with various vehicle-mounted positioning devices, such as differential global positioning system (GPS), inertial measurement unit (IMU), camera, laser radar, etc., and the positioning information fed back by these vehicle-mounted positioning devices is fused to finally determine the position coordinates of the vehicle.

[0003] The laser radar sensor is one of the important sensors on the automatic driving vehicle, which can obtain the point cloud information of the surrounding environment for perception, positioning and other functions. At present, the point cloud data of the laser radar is mainly used for vehicle positioning. However, in the wharf shore crane application scene, the shore crane will be adjusted and moved many times according to the position of the container during the operation of the actual ship. When the position of the shore crane changes, the actual point cloud position of the shore crane on the wharf surface will not match the position of the shore crane in the point cloud map of the wharf surface, which will affect the positioning result and even cause positioning failure, resulting in poor positioning accuracy. SUMMARY

[0004] The present application provides a relative positioning method, device, equipment and medium based on point cloud registration, which can improve the accuracy of vehicle positioning.

[0005] In a first aspect, the present application provides a relative positioning method based on point cloud registration, which comprises:

[0006] obtaining first point cloud data of a shore crane;

[0007] registering the first point cloud data of the shore crane with a pre-obtained shore crane point cloud map to obtain second point cloud data corresponding to the first point cloud data after registration;

[0008] obtaining a first current position of a vehicle, and determining a first coordinate position of the vehicle in a shore crane coordinate system according to the first current position and the second point cloud data, wherein the shore crane point cloud map comprises a coordinate position of the shore crane in the shore crane coordinate system;

[0009] converting the first coordinate position according to a pre-obtained coordinate position of the shore crane in a wharf coordinate system to obtain a second coordinate position of the vehicle in the wharf coordinate system.

[0010] In a second aspect, the present application provides a positioning device, which comprises:

[0011] The acquisition module is configured to acquire the first point cloud data of the quay crane.

[0012] The registration module is configured to register the first point cloud data of the quay crane with the pre-acquired quay crane point cloud map to obtain second point cloud data corresponding to the first point cloud data after registration.

[0013] The determination module is configured to acquire a first current position of the vehicle, and determine a first coordinate position of the vehicle in a quay crane coordinate system according to the first current position and the second point cloud data, the quay crane point cloud map including coordinate positions of the quay crane in the quay crane coordinate system.

[0014] The conversion module is configured to convert the first coordinate position according to a pre-acquired coordinate position of the quay crane in a terminal coordinate system to obtain a second coordinate position of the vehicle in the terminal coordinate system.

[0015] In a third aspect, an electronic device is provided, which includes a processor and a memory storing computer program instructions.

[0016] The processor implements the relative positioning method based on point cloud registration in any one of the embodiments of the first aspect when executing the computer program instructions.

[0017] In a fourth aspect, a computer storage medium is provided, which stores computer program instructions. The computer program instructions are executed by a processor to implement the relative positioning method based on point cloud registration in any one of the embodiments of the first aspect.

[0018] In a fifth aspect, a computer program product is provided. Instructions in the computer program product are executed by a processor of an electronic device to cause the electronic device to implement the relative positioning method based on point cloud registration in any one of the embodiments of the first aspect.

[0019] In a point cloud registration-based relative positioning method, device, equipment and medium provided by an embodiment of the present application, first point cloud data of a quay crane is obtained; the first point cloud data of the quay crane is registered with a pre-obtained quay crane point cloud map to obtain second point cloud data corresponding to the first point cloud data after registration; a first current position of a vehicle is obtained, and the first coordinate position of the vehicle in a quay crane coordinate system is determined according to the first current position and the second point cloud data; the quay crane point cloud map comprises a coordinate position of the quay crane in the quay crane coordinate system; the first coordinate position is converted according to a pre-obtained coordinate position of the quay crane in a terminal coordinate system to obtain a second coordinate position of the vehicle in the terminal coordinate system. In the foregoing manner, the first point cloud data of the quay crane and the quay crane point cloud map are registered to obtain an actual quay crane map (i.e. the second point cloud data), so that the first coordinate position of the vehicle in the quay crane coordinate system can be determined according to the actual quay crane point cloud map and the current position of the vehicle, and the relative position of the vehicle and the quay crane can be determined according to the first coordinate position and the coordinate position of the quay crane in the quay crane coordinate system, so that the second coordinate position of the vehicle in the terminal coordinate system can be determined according to the pre-obtained coordinate position of the quay crane in the terminal coordinate system, and thus the accuracy of vehicle positioning can be improved. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required to be used in the embodiments of the present application will be briefly introduced as follows, and other drawings can also be obtained by those of ordinary skill in the art without creative labor on the premise that they do not pay creative labor.

[0021] Figure 1 is a flowchart of a point cloud registration-based relative positioning method provided by an embodiment of the present application;

[0022] Figure 2 is a position diagram of a vehicle and a quay crane in an application scenario provided by an embodiment of the present application;

[0023] Figure 3 is another position diagram of a vehicle and a quay crane in an application scenario provided by an embodiment of the present application;

[0024] Figure 4 is a structural diagram of a positioning device provided by an embodiment of the present application;

[0025] Figure 5 is a structural diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to more clearly understand the above objectives, features and advantages of the present disclosure, the schemes of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0027] In the following description, a lot of specific details are set forth in order to provide a thorough understanding of the present disclosure, but the present disclosure can also be implemented in other different manners than those described herein; obviously, the embodiments described in the specification are only a part of the embodiments of the present disclosure, and not all the embodiments.

[0028] It should be noted that, in this document, the relationship terms such as “first” and “second” are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the term “comprise” or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device that includes a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such a process, method, article or device. Without more limitations, the element defined by the statement “comprises a……” does not exclude the presence of other identical elements in the process, method, article or device that includes the element.

[0029] In the prior art, the laser radar sensor is one of the important sensors on an autonomous vehicle, which can obtain point cloud information of the surrounding environment for perception, positioning and other functions. There are mainly two ways to use the point cloud data of the laser radar for positioning. One is to use the laser radar as a odometer. This method does not need to collect a high-precision point cloud map in advance, and only uses the point cloud data collected by the laser radar to provide a positioning result in a short time. However, long-term use will cause a serious drift phenomenon. The other is to use a point cloud registration algorithm to match a high-precision point cloud map collected in advance to obtain a relative position compared with the map. This method needs to collect a high-precision point cloud map in advance as a registration object, and can provide a globally consistent positioning result. In the current point cloud registration method technology applied to the port quay crane, before entering the wharf surface, the high-precision quay crane point cloud map collected in advance needs to be placed at each position of the wharf surface to form a point cloud map of the wharf surface. Then, the real-time point cloud data collected by the laser radar is matched with the point cloud map of the wharf surface for registration and positioning. For the wharf surface quay crane scene, the quay crane will be adjusted and moved many times according to the position of the container during the actual ship operation. However, the high-precision point cloud map of the quay crane cannot be moved in real time according to the position of the quay crane. In the current technical method, when the position of the quay crane changes, the actual point cloud position of the quay crane on the wharf surface does not match the position of the quay crane in the point cloud map of the wharf surface. At this time, the positioning result will be affected, and even the positioning fails.

[0030] To solve the problems in the prior art, the embodiments of the present application provide a relative positioning method based on point cloud registration, a device, equipment and medium. First, the relative positioning method based on point cloud registration provided by the embodiments of the present application is introduced.

[0031] Figure 1 The flowchart of the relative positioning method based on point cloud registration provided by one embodiment of the present application is shown. As shown in Figure 1 The method can specifically include the following steps:

[0032] S101, acquiring first point cloud data of a quay crane.

[0033] Optionally, in the embodiments of the present application, the quay crane refers to a mechanical device used for carrying goods, which is usually a large crane installed on a wharf and can move on the water surface to carry goods. Therefore, the position of the quay crane will change in actual application. The point cloud data is a data set composed of a large number of points in a three-dimensional space. Each point contains position information and optional other attribute information, such as color, normal vector, intensity, reflectivity, etc. The first point cloud data of the quay crane is a data set of the quay crane in a three-dimensional space.

[0034] Optionally, in the embodiments of the present application, point cloud data can be obtained in various ways, for example, it can be obtained by laser radar, which is a sensor mainly used to obtain point cloud data. It can generate a three-dimensional point cloud by emitting a laser beam and measuring its return time. Point cloud data can also be obtained by camera, using depth camera or stereo camera, which can capture the depth information of the scene, and then use computer algorithm to convert it into point cloud data. Or use radar to obtain point cloud data, where radar can detect objects in the scene by sending radio waves and measuring their return time. These data can be used to create point cloud. Commonly used radar is millimeter wave radar and the above-mentioned laser radar. Optionally, in the embodiments of the present application, point cloud data is usually transmitted to a computer or a cloud server for processing to extract scene information and for realizing automatic driving of the vehicle.

[0035] S102, the first point cloud data of the shore bridge is registered with the pre-acquired shore bridge point cloud map to obtain second point cloud data corresponding to the first point cloud data after registration.

[0036] Optionally, in the embodiments of the present application, a laser radar or other sensor can be installed on the shore bridge to collect point cloud data of the shore bridge. Combining these data with GPS or other positioning system data, a point cloud map of the shore bridge can be generated. Then feature points or feature lines are extracted from the two data sets (shore bridge point cloud map and first point cloud data), such as building corner points or road boundary lines. And use algorithms to match the features in the shore bridge point cloud map and the first point cloud data, such as least squares method or random sample consensus algorithm. By transforming the matched feature points, the transformation matrix between the first point cloud data and the shore bridge point cloud map is obtained. The first point cloud data is transformed using the transformation matrix to realize the registration with the shore bridge point cloud map, and the second point cloud data after registration is obtained. Through the above steps, the registration of the shore bridge point cloud data can be realized, and the second point cloud data after registration is obtained, which provides basic data support for subsequent analysis and application.

[0037] S103, the first current position of the vehicle is obtained, and the first coordinate position of the vehicle in the shore bridge coordinate system is determined according to the first current position and the second point cloud data, and the shore bridge point cloud map includes the coordinate position of the shore bridge in the shore bridge coordinate system.

[0038] Optionally, in a possible implementation manner of the present application, the first current position of the vehicle can be obtained by acquiring sensor data of the vehicle, such as a laser radar or a camera. By processing the sensor data, point cloud data of the vehicle at the current time point can be obtained. The point cloud data of the vehicle is filtered, registered, and the like, to obtain the current position of the vehicle. Of course, the current position of the vehicle can also be directly obtained by a GPS or other positioning tool. In the embodiment of the present application, since the shore-to-ship crane point cloud map includes the coordinate position of the shore-to-ship crane in the shore-to-ship crane coordinate system, the coordinate position of the vehicle in the shore-to-ship crane coordinate system can be calculated by measuring the distance and direction between the vehicle and the shore-to-ship crane. And the second coordinate position of the vehicle in the terminal coordinate system is obtained by accurately positioning the first coordinate position of the vehicle in the shore-to-ship crane coordinate system according to the second point cloud data.

[0039] In S104, the first coordinate position is converted to obtain the second coordinate position of the vehicle in the terminal coordinate system according to the pre-acquired coordinate position of the shore-to-ship crane in the terminal coordinate system.

[0040] Optionally, in a possible implementation manner of the present application, the coordinate transformation matrix between the shore-to-ship crane coordinate system and the terminal coordinate system can be determined by measuring the relative position relationship between the shore-to-ship crane and the terminal. For example, the coordinate transformation matrix between the shore-to-ship crane coordinate system and the terminal coordinate system can be calculated by measuring the position coordinates of the shore-to-ship crane and the terminal using a GPS or other measurement tool. The first coordinate position of the vehicle in the shore-to-ship crane coordinate system is multiplied by the coordinate transformation matrix to obtain the second coordinate position of the vehicle in the terminal coordinate system. It should be noted that when performing coordinate conversion and registration, the influence of factors such as sensor error and coordinate system inconsistency should be considered to ensure the accuracy and precision of the algorithm.

[0041] Optionally, in another possible implementation manner of the present application, as shown in Figure 2 , after the coordinate position of the shore-to-ship crane in the terminal coordinate system is acquired, the second coordinate position of the vehicle in the terminal coordinate system can be calculated according to the following formula (1).

[0042] pos p = pos r + pos c (1)

[0043] pos p represents the position of the vehicle in the terminal coordinate system, pos r represents the relative positioning result based on point cloud registration (i.e., the first coordinate position of the vehicle in the shore-to-ship crane coordinate system and the coordinate position of the shore-to-ship crane in the shore-to-ship crane coordinate system), and pos c represents the real-time position of the shore-to-ship crane (i.e., the real-time position of the shore-to-ship crane in the terminal coordinate system).

[0044] In an embodiment, wherein posr In the calculation, the wharf coordinate system is decoupled, the coordinate position of the input vehicle in the shore crane coordinate system is taken as the initial value of registration in the relative positioning process, then the real-time point cloud collected by the laser radar is registered with the shore crane point cloud, and the relative positioning result is continuously output, as shown in the following formula. Figure 3

[0045] When the vehicle is stationary and the shore crane position changes Δpos c When the vehicle is stationary and the shore crane is moving, the relative position of the vehicle to the shore crane is pos r -Δpos c , and the position of the shore crane in the wharf coordinate system at this time is pos c +Δpos c , then the position of the vehicle in the wharf surface coordinate system is:

[0046]

[0047] That is, when the vehicle is stationary and the shore crane is moving, the vehicle is still stationary in the wharf surface coordinate system, thereby avoiding the influence of the movement of the shore crane on the registration positioning.

[0048] When the vehicle advances Δpos r , the position of the vehicle in the wharf surface coordinate system at this time is:

[0049]

[0050] When the shore crane and the vehicle move at the same time:

[0051]

[0052] As can be seen from the above, no matter how the shore crane moves, the relative position of the vehicle to the shore crane can be obtained, and then the vehicle coordinates can be converted to the wharf surface coordinate system according to the real-time position of the shore crane, thereby making the relative positioning method based on point cloud registration proposed in the application improve the positioning accuracy without limiting the scene.

[0053] ​In the method for relative positioning based on point cloud registration provided in the embodiments of the present application, first point cloud data of a quay crane is obtained; the first point cloud data of the quay crane is registered with a pre-obtained quay crane point cloud map to obtain second point cloud data corresponding to the first point cloud data after registration; a first current position of a vehicle is obtained, and the first current position and the second point cloud data are used to determine a first coordinate position of the vehicle in a quay crane coordinate system; the quay crane point cloud map comprises a coordinate position of the quay crane in the quay crane coordinate system; the first coordinate position is converted according to a pre-obtained coordinate position of the quay crane in a terminal coordinate system to obtain a second coordinate position of the vehicle in the terminal coordinate system. In this way, the first point cloud data of the quay crane and the quay crane point cloud map are registered to obtain an actual quay crane map (i.e. the second point cloud data), so that the first coordinate position of the vehicle in the quay crane coordinate system can be determined according to the actual quay crane point cloud map and the current position of the vehicle, and the relative position of the vehicle and the quay crane can be determined according to the first coordinate position and the coordinate position of the quay crane in the quay crane coordinate system, so that the second coordinate position of the vehicle in the terminal coordinate system can be determined according to the pre-obtained coordinate position of the quay crane in the terminal coordinate system, and thus the accuracy of vehicle positioning can be improved even if the coordinate position of the quay crane changes in an actual scene.

[0054] In an embodiment, the step 101 can specifically include the following steps:

[0055] S1011, obtaining a second current position of the vehicle.

[0056] S1012, in a case where the second current position information is located in a preset range of the quay crane, obtaining first point cloud data of the quay crane.

[0057] Optionally, in a possible implementation manner of the present application, the first current position of the vehicle can be obtained by acquiring sensor data of the vehicle, such as a laser radar or a camera. The point cloud data of the vehicle at the current time point can be obtained by processing the sensor data. The current position of the vehicle can be obtained by filtering and registering the point cloud data of the vehicle. Of course, the current position of the vehicle can also be directly obtained by a GPS or other positioning tools. Then, by comparing the second current position of the vehicle with the pre-obtained quay crane position, it is determined whether the vehicle is in the preset range of the quay crane. If it is in the preset range, it is considered that the vehicle has reached the target position (i.e. in the range of the quay crane), and the vehicle can be stopped to collect the first point cloud data of the quay crane. If it is not in the preset range, the driving instruction is received until the vehicle reaches the target position and is stopped to collect the first point cloud data of the quay crane.

[0058] In these optional embodiments, whether the vehicle enters the range of the quay crane is determined by comparing the vehicle position and the quay crane position, so that the point cloud data is collected only when the vehicle travels in the range of the quay crane, thereby on the one hand, resource cost can be saved, and only the first point cloud data of the quay crane in the range of the quay crane is collected, the accuracy of the collected quay crane point cloud data is improved; on the other hand, all point cloud data on the wharf does not need to be collected, and the amount of calculation for subsequent registration positioning is saved.

[0059] In an embodiment, the above step 1012 can specifically include the following steps:

[0060] S10121, obtaining the Euclidean distance between the second current position and the coordinate position of the quay crane in the quay crane coordinate system;

[0061] S10122, obtaining the first point cloud data of the quay crane in the case where the Euclidean distance is in the preset threshold interval.

[0062] Optionally, in the embodiments of the present application, the Euclidean distance between the second current position of the vehicle and the coordinate position of the quay crane in the quay crane coordinate system can be calculated by the Euclidean distance calculation formula, wherein the specific calculation formula of the Euclidean distance can refer to the prior art, and the present application will not be repeated here.

[0063] Optionally, in the embodiments of the present application, if the Euclidean distance is in the threshold range, it can be considered that the vehicle has approached the target position, at which time the vehicle can be stopped, and the quay crane point cloud data can be collected. It is easy to understand that if the Euclidean distance is less than the lower limit of the preset threshold interval, it indicates that the vehicle has reached the target position, and the vehicle can also be stopped, and the quay crane point cloud data can be collected; if the Euclidean distance is greater than the upper limit of the threshold interval, it indicates that the vehicle is still far away from the quay crane, and needs to continue to advance; if the distance is in the threshold range, it can be considered that the vehicle has approached the target position.

[0064] Optionally, in the embodiments of the present application, the specific value of the preset threshold interval has been stored in the vehicle computer or the server, and can be obtained by reading a file or a network request.

[0065] In these optional embodiments, whether the vehicle enters the range of the quay crane is determined by calculating the Euclidean distance between the vehicle position and the quay crane position, and comparing with the set threshold, so that the point cloud data is collected only when the vehicle travels in the range of the quay crane, thereby on the one hand, resource cost can be saved, and only the first point cloud data of the quay crane in the range of the quay crane is collected, the accuracy of the collected quay crane point cloud data is improved; on the other hand, all point cloud data on the wharf does not need to be collected, and the amount of calculation for subsequent registration positioning is saved.

[0066] In an embodiment, the step 101 can specifically include the following steps:

[0067] S201, sending a first reflection signal to the surrounding environment of the vehicle through a transmitter of the vehicle.

[0068] S202, receiving target reflection information through a receiver of the vehicle, the target reflection signal being a signal reflected back by the first reflection signal.

[0069] Optionally, in a possible implementation manner of the present application, the first reflection signal can be sent to the surrounding environment of the vehicle through a transmitter of the vehicle, wherein the transmitter can be a sensor device such as a laser radar or a millimeter wave radar. These devices can emit high-frequency electromagnetic waves to the surrounding environment, and obtain the position, shape, distance, etc. of the obstacles in the surrounding environment by measuring the reflection signal of the electromagnetic wave. It should be noted that when using the radar device, appropriate transmission parameters and reception parameters need to be selected according to the working principle and characteristics of the device to obtain more accurate reflection signals.

[0070] S203, determining first point cloud data of the shore bridge according to the target reflection signal.

[0071] When receiving the target reflection information, the target reflection signal can be received through a receiver of the vehicle. The receiver can identify the target reflection signal according to the parameters of the radar transmitter and the characteristics of the reflection signal, and convert the signal into a digital signal for processing. The design and parameter setting of the receiver need to consider factors such as environmental noise and signal interference to ensure that the quality of the received reflection signal is good and can provide accurate target information. Then the device such as the laser radar or the millimeter wave radar measures the position, shape, distance, etc. of the obstacles in the surrounding environment and converts them into point cloud data. Through the point cloud data, the three-dimensional coordinates, shape, size, color, etc. of the obstacles can be represented, which can be used to establish a shore bridge point cloud map or for real-time positioning and perception.

[0072] In these optional embodiments, by receiving the target reflection signal, accurate target information can be provided to ensure that the quality of the obtained first point cloud data of the shore bridge is good, accurate target information can be provided, which provides accurate data support for subsequent registration positioning, and further improves the accuracy of positioning.

[0073] In an embodiment, the step according to 203 can specifically include the following steps:

[0074] S2031, determining initial point cloud data according to the target reflection signal.

[0075] Optionally, in a possible implementation manner of the present application, the laser beam can be emitted by the transmitter of the vehicle to scan the surrounding environment, the distance and the reflection intensity of the object surface are measured, and then an initial point cloud data is generated.

[0076] In S2032, the initial point cloud data is analyzed to obtain analyzed point cloud data.

[0077] In S2033, the analyzed point cloud data is calibrated according to preset installation parameters to obtain first point cloud data of the shore bridge, and the preset installation parameters include an installation position of the transmitter on the vehicle and a signal emission angle of the transmitter.

[0078] After the initial point cloud data is obtained, the initial point cloud data needs to be analyzed to obtain the position and other attribute information of each point, such as the reflection intensity and the color. The point cloud data is calibrated according to the preset installation parameters, and the calibration generally needs to perform rotation and translation transformation on the analyzed point cloud data to make it coincide with the actual coordinate system of the shore bridge. The calibration process can be realized by calibration or manual adjustment of parameters. The installation position of the transmitter on the vehicle and the signal emission angle of the transmitter are one of important parameters in the calibration process, which provides stable and accurate data support for obtaining the first point cloud data of the shore bridge, and further provides data support for subsequent registration and positioning.

[0079] Optionally, in a possible implementation manner of the present application, the transmitter can be a laser radar. The laser radar emits signals to the surrounding environment, receives the signals reflected by the target, determines the distance of the target by testing the running time of the reflected signals, and thus collects the point cloud data of the surrounding environment in real time. Then, the point cloud data is sent through the Ethernet in the User Datagram Protocol (UDP protocol). After receiving the corresponding point cloud data, the controller running the algorithm analyzes the point cloud data and performs alignment and calibration according to the installation parameters. The calibration formula is as follows:

[0080]

[0081] Wherein, x, y, z and φ, Θ, ψ are the installation position and the installation angle of the laser radar on the vehicle, P calibrated is the calibrated point cloud data, P raw is the initial point cloud data.

[0082] In these optional embodiments, by calibrating and analyzing the point cloud data, the quality of the first point cloud data of the shore bridge obtained can be ensured to be good, accurate target information can be provided, accurate data support is provided for subsequent registration and positioning, and the accuracy of positioning is further improved.

[0083] In an embodiment, the step 103 can be implemented as follows:

[0084] S1031, receiving the message information, the message information comprising a real-time position of the vehicle.

[0085] Optionally, in the embodiments of the present application, a network protocol can be used to communicate to obtain the message information, such as Transmission Control Protocol / Internet Protocol (TCP / IP) or UDP protocol. On the vehicle side, a corresponding network interface or socket can be used to receive the message information.

[0086] S1032, parsing the message information by using a database file to obtain a first current position of the vehicle.

[0087] Optionally, in the embodiments of the present application, a database or a parsing library can be used to parse the message information. Generally, the format of the message information is agreed by a standard or a protocol, and thus the message information can be parsed by using a corresponding parsing rule. Common parsing libraries include JavaScript Object Notation (JSON) and Database Can (DBC). Then, the real-time position information of the vehicle can be obtained according to the parsed message information. According to the format and structure of the database file, a corresponding query statement or Application Program Interface (API) can be used to obtain the first current position information of the vehicle.

[0088] Optionally, in a possible implementation manner of the present application, the vehicle position is sent in the form of a Controller Area Network (CAN) message, and the present application needs to receive the CAN message information comprising the vehicle position and parse the CAN message information by using the DBC file to obtain the vehicle position.

[0089] In these optional embodiments, the real-time current position of the vehicle is obtained by using the message information, so that the obtained vehicle position is more reliable and accurate, and accurate data support is provided for subsequent registration positioning.

[0090] In an embodiment, before the step 104, the method can further comprise the following steps:

[0091] S301, obtaining stored real-time port map information;

[0092] S302, determining real-time information of the quay crane according to the real-time terminal map information, the real-time information including a state of the quay crane and a position of the quay crane.

[0093] Optionally, the terminal refers to an area for berthing ships, carrying out cargo loading and unloading, and stacking.

[0094] Optionally, in a possible implementation manner of the present application, the real-time terminal map information can be acquired from a terminal map database. In the terminal map database, the real-time terminal map information should be updated in real time and include information such as the state and position of the quay crane. The state information can be whether the quay crane is moving, whether the quay crane is unloading or hoisting a container.

[0095] Optionally, in the embodiment of the present application, the specific position and state information of the quay crane can be acquired through an intelligent management system (Terminal Operation System, TOS) of the port and sent to the vehicle through a background.

[0096] Optionally, in the embodiment of the present application, according to the real-time terminal map information, the real-time information of the quay crane can be determined, including the state and position of the quay crane. The state information and position information can include parameters such as the type, height, lifting state, telescopic state, and rotating state of the quay crane, and the coordinate position of the quay crane in a quay crane coordinate system.

[0097] S303, determining the coordinate position of the quay crane in a terminal coordinate system in real time according to the real-time information of the quay crane.

[0098] According to the real-time information of the quay crane, the coordinate position of the quay crane in the terminal coordinate system can be determined in real time. Specifically, the real-time position of the quay crane can be first converted into the coordinate position of the quay crane in the quay crane coordinate system, and then the coordinate position of the quay crane in the terminal coordinate system can be calculated through the coordinate position of the quay crane in the quay crane coordinate system and the transformation relationship between the terminal coordinate system and the quay crane coordinate system.

[0099] In these optional embodiments, by acquiring the real-time map information of the terminal, the real-time position of the quay crane can be determined, providing an accurate reference benchmark for vehicle positioning and further improving the accuracy of positioning.

[0100] In an embodiment, the positioning can be performed through the following steps:

[0101] The point cloud data is acquired from the laser radar and calibrated. The laser radar collects the point cloud data of the surrounding environment in real time by emitting signals to the surroundings, receiving the signals reflected by the targets, and determining the distance of the targets by testing the running time of the reflected light, and then sends the point cloud data through Ethernet in UDP protocol. After receiving the corresponding point cloud data, the controller running the algorithm parses it and calibrates it according to the installation parameters.

[0102] Then the vehicle position is acquired from the signals of the vehicle, wherein the vehicle position is sent in the form of CAN message, and the CAN message containing the vehicle position needs to be received and parsed by the DBC file to obtain the vehicle position.

[0103] Then the shore crane information is acquired from the port TOS system, the specific position and state information of the shore crane is acquired through the intelligent management system (TOS) of the port, and is sent to the vehicle through the background, and the shore crane information needs to be received to determine whether it enters the range of shore crane registration positioning.

[0104] Then the position of the vehicle relative to the shore crane is calculated. After obtaining the vehicle position and the shore crane position, if the vehicle position enters the shore crane range, the relative registration positioning is started, and if not, it is waited. The Euclidean distance between the vehicle position and the shore crane position is calculated, and compared with the set threshold to determine whether it enters the shore crane range.

[0105] Then the multiple point clouds are registered to the same coordinate system through point cloud registration. If the coordinate system of a certain point cloud is known, the position information of other point clouds in the coordinate system can be obtained. In the present application, the shore crane point cloud data collected by the laser radar in real time is registered with the pre-prepared shore crane point cloud map to obtain the position of the laser radar in the shore crane point cloud coordinate, i.e. the relative position. The registration algorithm includes but is not limited to (Normal Distributions Transform (NDT), iterative closest point (ICP) and the like).

[0106] Then the relative positioning result is converted into absolute positioning result according to the shore crane position. The position of the laser radar in the shore crane point cloud coordinate, i.e. the relative position, is obtained, and the coordinate of the shore crane, i.e. the position of the shore crane in the entire wharf face coordinate system, is also obtained. Through the above formula (1), the position of the vehicle in the wharf face coordinate system can be obtained. At the same time, it is also shown in formulas 2, 3 and 4 that the relative positioning method based on point cloud registration in the present application can be registered and positioned according to the real-time moving shore crane.

[0107] Figure 4A structural schematic diagram of a positioning device provided by another embodiment of the present application is shown, and only parts related to the embodiments of the present application are shown for ease of illustration.

[0108] With reference to Figure 4 , the positioning device can include:

[0109] An acquisition module 401 is configured to acquire first point cloud data of a quay crane.

[0110] A registration module 402 is configured to register the first point cloud data of the quay crane with a pre-acquired quay crane point cloud map to obtain second point cloud data corresponding to the first point cloud data after registration.

[0111] A determination module 403 is configured to acquire a first current position of a vehicle, and determine a first coordinate position of the vehicle in a quay crane coordinate system according to the first current position and the second point cloud data, the quay crane point cloud map including coordinate positions of the quay crane in the quay crane coordinate system.

[0112] A conversion module 404 is configured to convert the first coordinate position according to a pre-acquired coordinate position of the quay crane in a terminal coordinate system to obtain a second coordinate position of the vehicle in the terminal coordinate system.

[0113] In an embodiment, the acquisition module 401 includes:

[0114] A first acquisition sub-module is configured to acquire a second current position of the vehicle.

[0115] A second acquisition sub-module is configured to acquire the first point cloud data of the quay crane in a case where the second current position information is located in a preset range of the quay crane.

[0116] In an embodiment, the second acquisition sub-module includes:

[0117] A first acquisition unit is configured to acquire a Euclidean distance between the second current position and a coordinate position of the quay crane in the quay crane coordinate system.

[0118] A second acquisition unit is configured to acquire the first point cloud data of the quay crane in a case where the Euclidean distance is located in a preset threshold interval.

[0119] In an embodiment, the acquisition module 401 includes:

[0120] A transmission sub-module is configured to send a first reflection signal to a surrounding environment of the vehicle through a transmitter of the vehicle.

[0121] A first receiving sub-module is configured to receive target reflection information through a receiver of the vehicle, the target reflection signal being a signal reflected back by the first reflection signal.

[0122] A first determination sub-module is configured to determine the first point cloud data of the quay crane according to the target reflection signal.

[0123] In an embodiment, the first determining sub-module comprises:

[0124] a first determining unit, configured to determine initial point cloud data according to the target reflection signal;

[0125] a parsing unit, configured to parse the initial point cloud data to obtain parsed point cloud data;

[0126] a calibration unit, configured to calibrate the parsed point cloud data according to preset installation parameters to obtain first point cloud data of the quay crane, the preset installation parameters comprising an installation position of the transmitter on the vehicle and a signal emission angle of the transmitter.

[0127] In an embodiment, the determining module 403 comprises:

[0128] a second receiving sub-module, configured to receive message information, the message information comprising a real-time position of the vehicle;

[0129] a first parsing sub-module, configured to parse the message information by using a database file to obtain a first current position of the vehicle.

[0130] In an embodiment, the positioning device can further comprise:

[0131] a second obtaining module, configured to obtain stored real-time port map information;

[0132] a second determining module, configured to determine real-time information of the quay crane according to the real-time port map information, the real-time information comprising a state of the quay crane and a position of the quay crane;

[0133] a third determining module, configured to determine a coordinate position of the quay crane in a port coordinate system in real time according to the real-time information of the quay crane.

[0134] It should be noted that the information interaction, execution process and the like between the above device / unit are based on the same concept as the battery thermal runaway early warning method, and the above device is corresponding to the battery thermal runaway early warning method. All the implementation manners in the above method embodiments are applicable to the embodiments of the device, and the specific functions and technical effects brought by the implementation manners can be referred to the method embodiments part, and will not be described here.

[0135] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above functional units and modules is taken as an example, and in actual application, the above functions can be completed by different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the above described functions. Each functional unit and module in the embodiment can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of software functional unit. In addition, the specific names of each functional unit and module are only for convenient distinction, and do not limit the protection scope of the present application. The specific working process of the units and modules in the system can refer to the corresponding process in the foregoing method embodiments, which will not be repeated here.

[0136] Figure 5 A hardware structure schematic diagram of an electronic device provided by an embodiment of the present application is shown.

[0137] The device can include a processor 501 and a memory 502 storing program instructions.

[0138] The processor 501 executes the program to implement the steps in any of the above method embodiments.

[0139] For example, the program can be divided into one or more modules / units, one or more modules / units are stored in the memory 502 and executed by the processor 501 to complete the present application. One or more modules / units can be a series of program instruction segments that can complete a specific function, which is used to describe the execution process of the program in the device.

[0140] Specifically, the above processor 501 can include a central processing unit (CPU), or a specific integrated circuit (ASIC), or can be configured as one or more integrated circuits that implement one or more embodiments of the present application.

[0141] The memory 502 can include mass storage for data or instructions. As an example and not by way of limitation, the memory 502 can include a hard disk drive (HDD), a floppy disk drive, flash memory, an optical disc (e.g., a compact disc (CD) or a digital versatile disc (DVD)), a solid-state drive (SSD), a USB drive, or a combination of two or more of these. Where appropriate, the memory 502 can include removable or non-removable (or fixed) media. Where appropriate, the memory 502 can be internal or external to the integrated gateway disaster recovery device. In particular embodiments, the memory 502 is non-volatile, solid-state memory.

[0142] The memory can include read-only memory (ROM), random-access memory (RAM), magnetic disk storage mediums, optical storage mediums, flash memory devices, electrical, optical, or other physical / tangible memory storage devices. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software that, when executed (by one or more processors), is operable to access the data and / or instructions as described with reference to the methods according to the aspects of the present disclosure.

[0143] The processor 501 implements any of the above-described methods by reading and executing program instructions stored in the memory 502.

[0144] In one example, the electronic device further includes a communication interface 503 and a bus 510. The processor 501, the memory 502, and the communication interface 503 are connected through the bus 510 and complete communication therebetween.

[0145] The communication interface 503 is mainly used to realize the communication between the modules, devices, units, and / or equipment in the embodiments of the present application.

[0146] Bus 510 includes hardware, software, or both, to couple components of the online data traffic metering device to each other and to couple components to other systems. For example, but not limited to, the bus can include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand (IB) interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association local (VLB) bus, or another suitable bus or a combination of two or more of these. Where suitable, bus 510 can include one or more buses. Although a particular bus is described and illustrated in this embodiment, the application contemplates any suitable bus or interconnect.

[0147] In addition, in combination with the method in the above-mentioned embodiments, the embodiments of the present application can provide a storage medium for implementation. The storage medium has program instructions stored thereon; the program instructions are executed by a processor to implement any of the methods in the above-mentioned embodiments.

[0148] The embodiments of the present application further provide a chip, which includes a processor and a communication interface, the communication interface is coupled to the processor, the processor is configured to execute programs or instructions, implement various processes of the above-mentioned method embodiments, and achieve the same technical effects. To avoid repetition, details are not described here.

[0149] It should be understood that the chip mentioned in the embodiments of the present application can also be referred to as a system-level chip, a system chip, a chip system, or a system-on-chip chip, etc.

[0150] The embodiments of the present application provide a computer program product, which is stored in a storage medium, and the program product is executed by at least one processor to implement various processes of the above-mentioned method embodiments, and achieve the same technical effects. To avoid repetition, details are not described here.

[0151] It should be understood that the present application is not limited to the specific configurations and processes described above and shown in the drawings. For the sake of brevity, detailed descriptions of well-known methods are omitted here. In the above-mentioned embodiments, several specific steps are described and shown as examples. However, the method processes of the present application are not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between steps, after understanding the spirit of the present application.

[0152] The functional modules shown in the structural block diagram above can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a functional card, and the like. When implemented in software, the elements of the present application are program or code segments that are used to perform the required tasks. The program or code segments can be stored in a machine-readable medium or transmitted through a data signal carried in a carrier wave over a transmission medium or communication link. The "machine-readable medium" can include any medium that can store or transfer information. Examples of the machine-readable medium include an electronic circuit, a semiconductor memory device, a ROM, a flash memory, an erasable ROM (EROM), a floppy diskette, a CD-ROM, an optical disk, a hard disk, a fiber optic medium, a radio frequency (RF) link, and the like. The code segments can be downloaded via a computer network, such as the Internet, an intranet, and the like.

[0153] It should also be noted that the example embodiments mentioned in the present application describe some methods or systems based on a series of steps or devices. However, the present application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiments, or in an order different from the embodiments, or several steps can be performed simultaneously.

[0154] The above describes the aspects of the present application with reference to the flowcharts and / or block diagrams of the methods, apparatuses (systems) and program products according to the embodiments of the present application. It should be understood that each block in the flowcharts and / or block diagrams, and the combination of blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus, to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus enable the implementation of the functions / actions specified in one or more blocks of the flowcharts and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It should also be understood that each block in the block diagrams and / or flowcharts, and the combination of blocks in the block diagrams and / or flowcharts, can also be implemented by special hardware that performs the specified functions or actions, or can be implemented by a combination of special hardware and computer instructions.

[0155] The above is only a specific implementation of the present application, and those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, modules and units can refer to the corresponding processes in the foregoing method embodiments, which will not be described here. It should be understood that the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be covered within the protection scope of the present application.

Claims

1. A relative positioning method based on point cloud registration, characterized in that, The method includes: Obtain the first point cloud data of the quay crane; The first point cloud data of the quay crane is registered with the pre-acquired quay crane point cloud map to obtain the second point cloud data corresponding to the first point cloud data after registration. The vehicle's first current position is obtained, and based on the first current position and the second point cloud data, the vehicle's first coordinate position in the quay crane coordinate system is determined. The quay crane point cloud map includes the coordinate position of the quay crane in the quay crane coordinate system. Based on the pre-acquired coordinate position of the quay crane in the terminal coordinate system, the first coordinate position is transformed to obtain the second coordinate position of the vehicle in the terminal coordinate system; Determining the first coordinate position of the vehicle in the quay crane coordinate system based on the first current position and the second point cloud data includes: By measuring the distance and direction between the vehicle and the quay crane, the coordinate position of the vehicle in the quay crane coordinate system is calculated, and the vehicle is accurately located based on the second point cloud data to find the first coordinate position of the vehicle in the quay crane coordinate system. The step of transforming the first coordinate position based on the pre-acquired coordinate position of the quay crane in the terminal coordinate system to obtain the second coordinate position of the vehicle in the terminal coordinate system includes: By measuring the relative positional relationship between the quay crane and the wharf, the coordinate transformation matrix between the quay crane coordinate system and the wharf coordinate system is determined; by multiplying the first coordinate position of the vehicle in the quay crane coordinate system with the coordinate transformation matrix, the second coordinate position of the vehicle in the wharf coordinate system is obtained.

2. The method according to claim 1, characterized in that, The acquisition of the first point cloud data of the quay crane includes: Obtain the second current position of the vehicle; If the second current location information is within a preset range of the quay bridge, the first point cloud data of the quay bridge is acquired.

3. The method according to claim 2, characterized in that, When the second current position is within a preset range of the quay crane, acquiring the first point cloud data of the quay crane includes: Obtain the Euclidean distance between the second current position and the coordinate position of the quay crane in the quay crane coordinate system; When the Euclidean distance is within a preset threshold range, the first point cloud data of the quay bridge is acquired.

4. The method according to claim 1, characterized in that, The acquisition of the first point cloud data of the quay crane includes: The vehicle transmits a first reflected signal to the environment surrounding the vehicle via its transmitter. The target reflected signal is received by the vehicle's receiver; the target reflected signal is the signal reflected back by the first reflected signal. The first point cloud data of the quay bridge is determined based on the target reflection signal.

5. The method according to claim 4, characterized in that, The step of determining the first point cloud data of the quay crane based on the target reflection signal includes: The initial point cloud data is determined based on the target reflection signal; The initial point cloud data is parsed to obtain the parsed point cloud data; The parsed point cloud data is calibrated according to preset installation parameters to obtain the first point cloud data of the quay crane. The preset installation parameters include the installation position of the transmitter on the vehicle and the signal transmission angle of the transmitter.

6. The method according to claim 1, characterized in that, Obtaining the first current location of the vehicle includes: Receive message information, the message information including the real-time location of the vehicle; The message information is parsed using a database file to obtain the vehicle's first current location.

7. The method according to claim 1, characterized in that, Before transforming the first coordinate position based on the pre-acquired coordinate position of the quay crane in the terminal coordinate system, the method further includes: Retrieve stored real-time dock map information; Based on the real-time terminal map information, the real-time information of the quay crane is determined, including the status and location of the quay crane. Based on the real-time information of the quay crane, the coordinate position of the quay crane in the dock coordinate system is determined in real time.

8. A positioning device, characterized in that, The device includes: The acquisition module is used to acquire the first point cloud data of the quay crane; The registration module is used to register the first point cloud data of the quay crane with the pre-acquired quay crane point cloud map to obtain the second point cloud data corresponding to the first point cloud data after registration. The determination module is used to obtain the first current position of the vehicle and determine the first coordinate position of the vehicle in the quay crane coordinate system based on the first current position and the second point cloud data. The quay crane point cloud map includes the coordinate position of the quay crane in the quay crane coordinate system. The conversion module is used to convert the first coordinate position according to the pre-acquired coordinate position of the quay crane in the terminal coordinate system to obtain the second coordinate position of the vehicle in the terminal coordinate system. The determining module is specifically used for: By measuring the distance and direction between the vehicle and the quay crane, the coordinate position of the vehicle in the quay crane coordinate system is calculated, and the vehicle is accurately located based on the second point cloud data to find the first coordinate position of the vehicle in the quay crane coordinate system. The conversion module is specifically used for: By measuring the relative positional relationship between the quay crane and the wharf, the coordinate transformation matrix between the quay crane coordinate system and the wharf coordinate system is determined; by multiplying the first coordinate position of the vehicle in the quay crane coordinate system with the coordinate transformation matrix, the second coordinate position of the vehicle in the wharf coordinate system is obtained.

9. An electronic device, characterized in that, The device includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, it implements the relative positioning method based on point cloud registration as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions, which, when executed by a processor, implement the relative positioning method based on point cloud registration as described in any one of claims 1-7.

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